GPT-4 Turbo vs Ternary Bonsai 2 27B
Ternary Bonsai 2 27B costs 60.0x less per output token than GPT-4 Turbo ($0.50 vs $30.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $30.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.50
GPT-4 Turbo or Ternary Bonsai 2 27B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. GPT-4 Turbo has results on AA Coding Index, LiveCodeBench (Artificial Analysis run) and LMArena Text: coding; Ternary Bonsai 2 27B has none yet. Compare them on price and context instead.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only GPT-4 Turbo has a AA Intelligence Index result, 7.0.
Directional only
Long documents
Listed context window
Ternary Bonsai 2 27B
Ternary Bonsai 2 27B takes 262K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ternary Bonsai 2 27B
GPT-4 Turbo $0.025, Ternary Bonsai 2 27B $0.0003 per turn.
List prices
At a glance
- Coding index
- GPT-4 Turbo not benchmarked, Ternary Bonsai 2 27B not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- GPT-4 Turbo $30.00 against Ternary Bonsai 2 27B $0.50 per million output tokens, 60.0x apart.
- Context window
- GPT-4 Turbo takes 128K tokens, Ternary Bonsai 2 27B 262K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards measured
| Benchmark | GPT-4 Turbo | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| AA Coding Index | 21.5 | Not measured | Only GPT-4 Turbo measured |
| LiveCodeBench (Artificial Analysis run) | 29.1% | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: coding | 1268 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: software and IT | 1267 | Not measured | Only GPT-4 Turbo measured |
| Neither model has a result on the other 39 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-4 Turbo | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.0 | Not measured | Only GPT-4 Turbo measured |
| Epoch Capabilities Index | 127.3 | Not measured | Only GPT-4 Turbo measured |
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | GPT-4 Turbo | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| Humanity's Last Exam (Artificial Analysis run) | 3.1% | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: hard prompts | 1251 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: expert | 1223 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: hard prompts in English | 1266 | Not measured | Only GPT-4 Turbo measured |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-4 Turbo | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| LMArena Text: math | 1272 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: mathematical work | 1268 | Not measured | Only GPT-4 Turbo measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | GPT-4 Turbo | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 80.5% | Not measured | Only GPT-4 Turbo measured |
| MedQA (Vals AI) | 82.0% | Not measured | Only GPT-4 Turbo measured |
| MMLU Pro (Artificial Analysis run) | 69.4% | Not measured | Only GPT-4 Turbo measured |
| MMLU | 81.3% | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: science | 1256 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: medicine and healthcare | 1239 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: legal and government | 1265 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: business and finance | 1222 | Not measured | Only GPT-4 Turbo measured |
| Neither model has a result on the other 12 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index22 boards measured
| Benchmark | GPT-4 Turbo | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| DTBench | 61.6% | Not measured | Only GPT-4 Turbo measured |
| LMCA | 9.8% | Not measured | Only GPT-4 Turbo measured |
| LMArena Text | 1272 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: instruction following | 1249 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: creative writing | 1268 | Not measured | Only GPT-4 Turbo measured |
| LMArena Vision | 1090 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: English | 1291 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: non-English | 1245 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: Chinese | 1242 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: German | 1259 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: Japanese | 1194 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: Korean | 1187 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: French | 1276 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: Spanish | 1260 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: Russian | 1259 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: Polish | 1302 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: multi-turn | 1267 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: longer queries | 1254 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: writing and language | 1279 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: entertainment and media | 1258 | Not measured | Only GPT-4 Turbo measured |
| LMArena Vision: English | 1097 | Not measured | Only GPT-4 Turbo measured |
| LMArena Vision: Chinese | 1045 | Not measured | Only GPT-4 Turbo measured |
| Neither model has a result on the other 26 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Ternary Bonsai 2 27B costs less
Repository review
50K input + 3K output tokens
Ternary Bonsai 2 27B costs less
Agent loop
200K input + 10K output tokens
Ternary Bonsai 2 27B costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI GPT-4 Turbo | PrismML Ternary Bonsai 2 27B |
|---|---|---|
| Maker | OpenAI | Prism-ml |
| Weights | No public weights listed | Open weights |
| Released | April 9, 2024 | September 18, 2026 |
| Context window | 128K | 262K |
| Input $/Mtok | $10.00 | $0.075 |
| Output $/Mtok | $30.00 | $0.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4 Turbo better than Ternary Bonsai 2 27B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, GPT-4 Turbo or Ternary Bonsai 2 27B?
GPT-4 Turbo costs $10.00 per million input tokens and $30.00 per million output tokens; Ternary Bonsai 2 27B costs $0.075 and $0.50. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4 Turbo or Ternary Bonsai 2 27B?
Ternary Bonsai 2 27B, with 262K tokens against 128K.
Has any benchmark tested both GPT-4 Turbo and Ternary Bonsai 2 27B?
No benchmark has tested both yet. GPT-4 Turbo has results on AA Coding Index, LiveCodeBench (Artificial Analysis run) and LMArena Text: coding; Ternary Bonsai 2 27B has none yet. Compare them on price and context instead. Data as of October 22, 2026.